{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The QLBS model for a European option\n",
    "\n",
    "Welcome to your 2nd assignment in Reinforcement Learning in Finance. In this exercise you will arrive to an option price and the hedging portfolio via standard toolkit of Dynamic Pogramming (DP).\n",
    "QLBS model learns both the optimal option price and optimal hedge directly from trading data.\n",
    "\n",
    "**Instructions:**\n",
    "- You will be using Python 3.\n",
    "- Avoid using for-loops and while-loops, unless you are explicitly told to do so.\n",
    "- Do not modify the (# GRADED FUNCTION [function name]) comment in some cells. Your work would not be graded if you change this. Each cell containing that comment should only contain one function.\n",
    "- After coding your function, run the cell right below it to check if your result is correct.\n",
    "- When encountering **```# dummy code - remove```** please replace this code with your own \n",
    "\n",
    "\n",
    "**After this assignment you will:**\n",
    " - Re-formulate option pricing and hedging method using the language of Markov Decision Processes (MDP)\n",
    " - Setup foward simulation using Monte Carlo\n",
    " - Expand optimal action (hedge) $a_t^\\star(X_t)$ and optimal Q-function $Q_t^\\star(X_t, a_t^\\star)$ in basis functions with time-dependend coefficients\n",
    "\n",
    "Let's get started!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## About iPython Notebooks ##\n",
    "\n",
    "iPython Notebooks are interactive coding environments embedded in a webpage. You will be using iPython notebooks in this class. You only need to write code between the ### START CODE HERE ### and ### END CODE HERE ### comments. After writing your code, you can run the cell by either pressing \"SHIFT\"+\"ENTER\" or by clicking on \"Run Cell\" (denoted by a play symbol) in the upper bar of the notebook. \n",
    "\n",
    "We will often specify \"(≈ X lines of code)\" in the comments to tell you about how much code you need to write. It is just a rough estimate, so don't feel bad if your code is longer or shorter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#import warnings\n",
    "#warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy.stats import norm\n",
    "import random\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "\n",
    "sys.path.append(\"..\")\n",
    "import grading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "### ONLY FOR GRADING. DO NOT EDIT ###\n",
    "submissions=dict()\n",
    "assignment_key=\"wLtf3SoiEeieSRL7rCBNJA\" \n",
    "all_parts=[\"15mYc\", \"h1P6Y\", \"q9QW7\",\"s7MpJ\",\"Pa177\"]\n",
    "### ONLY FOR GRADING. DO NOT EDIT ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "COURSERA_TOKEN =  ''# the key provided to the Student under his/her email on submission page\n",
    "COURSERA_EMAIL = '' # the email"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parameters for MC simulation of stock prices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "S0 = 100      # initial stock price\n",
    "mu = 0.05     # drift\n",
    "sigma = 0.15  # volatility\n",
    "r = 0.03      # risk-free rate\n",
    "M = 1         # maturity\n",
    "\n",
    "T = 24        # number of time steps\n",
    "N_MC = 10000  # number of paths\n",
    "\n",
    "delta_t = M / T                # time interval\n",
    "gamma = np.exp(- r * delta_t)  # discount factor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Black-Sholes Simulation\n",
    "Simulate $N_{MC}$ stock price sample paths with $T$ steps by the classical Black-Sholes formula.\n",
    "\n",
    "$$dS_t=\\mu S_tdt+\\sigma S_tdW_t\\quad\\quad S_{t+1}=S_te^{\\left(\\mu-\\frac{1}{2}\\sigma^2\\right)\\Delta t+\\sigma\\sqrt{\\Delta t}Z}$$\n",
    "\n",
    "where $Z$ is a standard normal random variable.\n",
    "\n",
    "Based on simulated stock price $S_t$ paths, compute state variable $X_t$ by the following relation.\n",
    "\n",
    "$$X_t=-\\left(\\mu-\\frac{1}{2}\\sigma^2\\right)t\\Delta t+\\log S_t$$\n",
    "\n",
    "Also compute\n",
    "\n",
    "$$\\Delta S_t=S_{t+1}-e^{r\\Delta t}S_t\\quad\\quad \\Delta\\hat{S}_t=\\Delta S_t-\\Delta\\bar{S}_t\\quad\\quad t=0,...,T-1$$\n",
    "\n",
    "where $\\Delta\\bar{S}_t$ is the sample mean of all values of $\\Delta S_t$.\n",
    "\n",
    "Plots of 5 stock price $S_t$ and state variable $X_t$ paths are shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Time Cost: 0.18503808975219727 seconds\n"
     ]
    }
   ],
   "source": [
    "# make a dataset\n",
    "starttime = time.time()\n",
    "np.random.seed(42)\n",
    "\n",
    "# stock price\n",
    "S = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "S.loc[:,0] = S0\n",
    "\n",
    "# standard normal random numbers\n",
    "RN = pd.DataFrame(np.random.randn(N_MC,T), index=range(1, N_MC+1), columns=range(1, T+1))\n",
    "\n",
    "for t in range(1, T+1):\n",
    "    S.loc[:,t] = S.loc[:,t-1] * np.exp((mu - 1/2 * sigma**2) * delta_t + sigma * np.sqrt(delta_t) * RN.loc[:,t])\n",
    "\n",
    "delta_S = S.loc[:,1:T].values - np.exp(r * delta_t) * S.loc[:,0:T-1]\n",
    "delta_S_hat = delta_S.apply(lambda x: x - np.mean(x), axis=0)\n",
    "\n",
    "# state variable\n",
    "X = - (mu - 1/2 * sigma**2) * np.arange(T+1) * delta_t + np.log(S)   # delta_t here is due to their conventions\n",
    "\n",
    "endtime = time.time()\n",
    "print('\\nTime Cost:', endtime - starttime, 'seconds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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5eTmXMZ/vYv6u87z7Swz3frGbmEu5dYohJbeY11afICLAhedHdqjTMSyp2mQv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Rzenk/sNeEdFugBBsdHgBkSfj53615KyYHfsvly4W6MlbVc+9BArpje65yLmEcM9GXqP4bg4unA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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f459188ada0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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oDwQ+wLs93iUxP5Fxm8YR4BDAT0N+Qq1q2pVKm4rqJIaqtHkKbiSF6+KAghpF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TYoj+KEugZ7ce3fRxI+wJ9t/0vlp5UpWMzW9i5Wp7ZnXTpaNw2jLo9s1eN0DfYirH9XErfnY7V2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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f458f0e9128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot 10 paths\n",
    "step_size = N_MC // 10\n",
    "idx_plot = np.arange(step_size, N_MC, step_size)\n",
    "\n",
    "plt.plot(S.T.iloc[:,idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.title('Stock Price Sample Paths')\n",
    "plt.show()\n",
    "\n",
    "plt.plot(X.T.iloc[:,idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.ylabel('State Variable')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define function *terminal_payoff* to compute the terminal payoff of a European put option.\n",
    "\n",
    "$$H_T\\left(S_T\\right)=\\max\\left(K-S_T,0\\right)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def terminal_payoff(ST, K):\n",
    "    # ST   final stock price\n",
    "    # K    strike\n",
    "    payoff = max(K - ST, 0)\n",
    "    return payoff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(delta_S)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Define spline basis functions  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X.shape =  (10000, 25)\n",
      "X_min, X_max =  4.0249235249 5.19080277513\n",
      "Number of points k =  17\n"
     ]
    },
    {
     "data": {
      "image/png": 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Kd1ORaaKhbyLIp2sAVGo46wvQcYB3jj9EzUANd266kzhN9LZ885Nu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\nDnK5m5l1kMvdzKyDXO5mZh30B+QS+Eik+OaeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f458f054b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import bspline\n",
    "import bspline.splinelab as splinelab\n",
    "\n",
    "X_min = np.min(np.min(X))\n",
    "X_max = np.max(np.max(X))\n",
    "print('X.shape = ', X.shape)\n",
    "print('X_min, X_max = ', X_min, X_max)\n",
    "\n",
    "p = 4              # order of spline (as-is; 3 = cubic, 4: B-spline?)\n",
    "ncolloc = 12\n",
    "\n",
    "tau = np.linspace(X_min,X_max,ncolloc)  # These are the sites to which we would like to interpolate\n",
    "\n",
    "# k is a knot vector that adds endpoints repeats as appropriate for a spline of order p\n",
    "# To get meaninful results, one should have ncolloc >= p+1\n",
    "k = splinelab.aptknt(tau, p) \n",
    "                             \n",
    "# Spline basis of order p on knots k\n",
    "basis = bspline.Bspline(k, p)        \n",
    "        \n",
    "f = plt.figure()\n",
    "# B   = bspline.Bspline(k, p)     # Spline basis functions \n",
    "print('Number of points k = ', len(k))\n",
    "basis.plot()\n",
    "\n",
    "plt.savefig('Basis_functions.png', dpi=600)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "bspline.bspline.Bspline"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(basis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 25)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.values.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make data matrices with feature values\n",
    "\n",
    "\"Features\" here are the values of basis functions at data points\n",
    "The outputs are 3D arrays of dimensions num_tSteps x num_MC x num_basis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "num_basis =  12\n",
      "dim data_mat_t =  (25, 10000, 12)\n",
      "Computational time: 100.16060328483582 seconds\n"
     ]
    }
   ],
   "source": [
    "num_t_steps = T + 1\n",
    "num_basis =  ncolloc # len(k) #\n",
    "\n",
    "data_mat_t = np.zeros((num_t_steps, N_MC,num_basis ))\n",
    "print('num_basis = ', num_basis)\n",
    "print('dim data_mat_t = ', data_mat_t.shape)\n",
    "\n",
    "t_0 = time.time()\n",
    "# fill it \n",
    "for i in np.arange(num_t_steps):\n",
    "    x = X.values[:,i]\n",
    "    data_mat_t[i,:,:] = np.array([ basis(el) for el in x ])\n",
    "\n",
    "t_end = time.time()\n",
    "print('Computational time:', t_end - t_0, 'seconds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# save these data matrices for future re-use\n",
    "np.save('data_mat_m=r_A_%d' % N_MC, data_mat_t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(25, 10000, 12)\n",
      "17\n"
     ]
    }
   ],
   "source": [
    "print(data_mat_t.shape)  # shape num_steps x N_MC x num_basis\n",
    "print(len(k))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dynamic Programming solution for QLBS \n",
    "\n",
    "The MDP problem in this case is to solve the following Bellman optimality equation for the action-value function.\n",
    "\n",
    "$$Q_t^\\star\\left(x,a\\right)=\\mathbb{E}_t\\left[R_t\\left(X_t,a_t,X_{t+1}\\right)+\\gamma\\max_{a_{t+1}\\in\\mathcal{A}}Q_{t+1}^\\star\\left(X_{t+1},a_{t+1}\\right)\\space|\\space X_t=x,a_t=a\\right],\\space\\space t=0,...,T-1,\\quad\\gamma=e^{-r\\Delta t}$$\n",
    "\n",
    "where $R_t\\left(X_t,a_t,X_{t+1}\\right)$ is the one-step time-dependent random reward and $a_t\\left(X_t\\right)$ is the action (hedge).\n",
    "\n",
    "Detailed steps of solving this equation by Dynamic Programming are illustrated below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With this set of basis functions $\\left\\{\\Phi_n\\left(X_t^k\\right)\\right\\}_{n=1}^N$, expand the optimal action (hedge) $a_t^\\star\\left(X_t\\right)$ and optimal Q-function $Q_t^\\star\\left(X_t,a_t^\\star\\right)$ in basis functions with time-dependent coefficients.\n",
    "$$a_t^\\star\\left(X_t\\right)=\\sum_n^N{\\phi_{nt}\\Phi_n\\left(X_t\\right)}\\quad\\quad Q_t^\\star\\left(X_t,a_t^\\star\\right)=\\sum_n^N{\\omega_{nt}\\Phi_n\\left(X_t\\right)}$$\n",
    "\n",
    "Coefficients $\\phi_{nt}$ and $\\omega_{nt}$ are computed recursively backward in time for $t=T−1,...,0$. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Coefficients for expansions of the optimal action $a_t^\\star\\left(X_t\\right)$ are solved by\n",
    "\n",
    "$$\\phi_t=\\mathbf A_t^{-1}\\mathbf B_t$$\n",
    "\n",
    "where $\\mathbf A_t$ and $\\mathbf B_t$ are matrix and vector respectively with elements given by\n",
    "\n",
    "$$A_{nm}^{\\left(t\\right)}=\\sum_{k=1}^{N_{MC}}{\\Phi_n\\left(X_t^k\\right)\\Phi_m\\left(X_t^k\\right)\\left(\\Delta\\hat{S}_t^k\\right)^2}\\quad\\quad B_n^{\\left(t\\right)}=\\sum_{k=1}^{N_{MC}}{\\Phi_n\\left(X_t^k\\right)\\left[\\hat\\Pi_{t+1}^k\\Delta\\hat{S}_t^k+\\frac{1}{2\\gamma\\lambda}\\Delta S_t^k\\right]}$$\n",
    "\n",
    "$$\\Delta S_t=S_{t+1} - e^{-r\\Delta t} S_t\\space \\quad t=T-1,...,0$$\n",
    "where $\\Delta\\hat{S}_t$ is the sample mean of all values of $\\Delta S_t$.\n",
    "\n",
    "Define function *function_A* and *function_B* to compute the value of matrix $\\mathbf A_t$ and vector $\\mathbf B_t$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define the option strike and risk aversion parameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "risk_lambda = 0.001 # risk aversion\n",
    "K = 100             # option stike  \n",
    "\n",
    "# Note that we set coef=0 below in function function_B_vec. This correspond to a pure risk-based hedging"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Part 1 Calculate coefficients  $\\phi_{nt}$ of the optimal action $a_t^\\star\\left(X_t\\right)$\n",
    "\n",
    "**Instructions:**\n",
    "- implement function_A_vec() which computes $A_{nm}^{\\left(t\\right)}$ matrix\n",
    "- implement function_B_vec() which computes $B_n^{\\left(t\\right)}$ column vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# functions to compute optimal hedges\n",
    "def function_A_vec(t, delta_S_hat, data_mat, reg_param):\n",
    "    \"\"\"\n",
    "    function_A_vec - compute the matrix A_{nm} from Eq. (52) (with a regularization!)\n",
    "    Eq. (52) in QLBS Q-Learner in the Black-Scholes-Merton article\n",
    "    \n",
    "    Arguments:\n",
    "    t - time index, a scalar, an index into time axis of data_mat\n",
    "    delta_S_hat - pandas.DataFrame of dimension N_MC x T\n",
    "    data_mat - pandas.DataFrame of dimension T x N_MC x num_basis\n",
    "    reg_param - a scalar, regularization parameter\n",
    "    \n",
    "    Return:\n",
    "    - np.array, i.e. matrix A_{nm} of dimension num_basis x num_basis\n",
    "    \"\"\"\n",
    "    \n",
    "    ### START CODE HERE ### (≈ 5-6 lines of code)\n",
    "    # store result in A_mat for grading\n",
    "    X_mat = data_mat[t, :, :]\n",
    "    num_basis_funcs = X_mat.shape[1]\n",
    "    this_dS = delta_S_hat.loc[:, t]\n",
    "    hat_dS2 = (this_dS ** 2).reshape(-1, 1)\n",
    "    A_mat = np.dot(X_mat.T, X_mat * hat_dS2) + reg_param * np.eye(num_basis_funcs)\n",
    "    ### END CODE HERE ###\n",
    "    return A_mat\n",
    "   \n",
    "        \n",
    "def function_B_vec(t, \n",
    "                   Pi_hat, \n",
    "                   delta_S_hat=delta_S_hat, \n",
    "                   S=S, \n",
    "                   data_mat=data_mat_t,\n",
    "                   gamma=gamma,\n",
    "                   risk_lambda=risk_lambda):\n",
    "    \"\"\"\n",
    "    function_B_vec - compute vector B_{n} from Eq. (52) QLBS Q-Learner in the Black-Scholes-Merton article\n",
    "    \n",
    "    Arguments:\n",
    "    t - time index, a scalar, an index into time axis of delta_S_hat\n",
    "    Pi_hat - pandas.DataFrame of dimension N_MC x T of portfolio values \n",
    "    delta_S_hat - pandas.DataFrame of dimension N_MC x T\n",
    "    S - pandas.DataFrame of simulated stock prices of dimension N_MC x T\n",
    "    data_mat - pandas.DataFrame of dimension T x N_MC x num_basis\n",
    "    gamma - one time-step discount factor $exp(-r \\delta t)$\n",
    "    risk_lambda - risk aversion coefficient, a small positive number\n",
    "    Return:\n",
    "    np.array() of dimension num_basis x 1\n",
    "    \"\"\"\n",
    "#     coef = 1.0/(2 * gamma * risk_lambda)\n",
    "    # override it by zero to have pure risk hedge\n",
    "    \n",
    "    ### START CODE HERE ### (≈ 5-6 lines of code)\n",
    "    # store result in B_vec for grading\n",
    "    tmp = Pi_hat.loc[:,t+1] * delta_S_hat.loc[:, t]\n",
    "    X_mat = data_mat[t, :, :]  # matrix of dimension N_MC x num_basis\n",
    "    B_vec = np.dot(X_mat.T, tmp)\n",
    "    ### END CODE HERE ###\n",
    "    return B_vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/ipykernel/__main__.py:22: FutureWarning: reshape is deprecated and will raise in a subsequent release. Please use .values.reshape(...) instead\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submission successful, please check on the coursera grader page for the status\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 12261.42554869,   1259.28492179,    176.92982137,  11481.78830269,\n",
       "         6579.62177219,  12261.42554869,    628.29798339,    189.70711815,\n",
       "        12261.42554869,    176.92982137,    176.92982137,  11481.78830269,\n",
       "         6579.62177219,   1259.28492179,  11481.78830269,  11481.78830269,\n",
       "          189.70711815,  10408.62274335,   6579.62177219,     18.31727282,\n",
       "        11481.78830269,     32.94988345,  10408.62274335,     18.31727282,\n",
       "           32.94988345,   6579.62177219,     16.09789819,     32.94988345,\n",
       "          628.29798339,  10408.62274335,     32.94988345,   3275.69869791,\n",
       "           16.09789819,    176.92982137,    176.92982137,    628.29798339,\n",
       "           32.94988345,     32.94988345,    189.70711815,     32.94988345,\n",
       "        12261.42554869,   1259.28492179,   3275.69869791,    189.70711815,\n",
       "         6579.62177219,    189.70711815,  12261.42554869,   6579.62177219,\n",
       "         3275.69869791,  12261.42554869])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### GRADED PART (DO NOT EDIT) ###\n",
    "reg_param = 1e-3\n",
    "np.random.seed(42)\n",
    "\n",
    "A_mat = function_A_vec(T-1, delta_S_hat, data_mat_t, reg_param)\n",
    "idx_row = np.random.randint(low=0, high=A_mat.shape[0], size=50)\n",
    "\n",
    "np.random.seed(42)\n",
    "idx_col = np.random.randint(low=0, high=A_mat.shape[1], size=50)\n",
    "\n",
    "\n",
    "part_1 = list(A_mat[idx_row, idx_col])\n",
    "try:\n",
    "    part1 = \" \".join(map(repr, part_1))\n",
    "except TypeError:\n",
    "    part1 = repr(part_1)\n",
    "\n",
    "\n",
    "submissions[all_parts[0]]=part1\n",
    "grading.submit(COURSERA_EMAIL, COURSERA_TOKEN, assignment_key,all_parts[:1],all_parts,submissions)\n",
    "A_mat[idx_row, idx_col]\n",
    "### GRADED PART (DO NOT EDIT) ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submission successful, please check on the coursera grader page for the status\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([  3.29073713e+01,  -2.95729027e+02,  -8.73272905e+02,\n",
       "        -3.31856654e+03,  -1.25928899e+04,  -1.14032852e+04,\n",
       "        -2.91636810e+03,  -3.38216415e+00,  -1.33830723e+02,\n",
       "        -1.36875328e+02,  -6.60942460e+01,  -3.07904971e+01])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### GRADED PART (DO NOT EDIT) ###\n",
    "np.random.seed(42)\n",
    "risk_lambda = 0.001\n",
    "Pi = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "Pi.iloc[:,-1] = S.iloc[:,-1].apply(lambda x: terminal_payoff(x, K))\n",
    "\n",
    "Pi_hat = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "Pi_hat.iloc[:,-1] = Pi.iloc[:,-1] - np.mean(Pi.iloc[:,-1])\n",
    "B_vec = function_B_vec(T-1, Pi_hat, delta_S_hat, S, data_mat_t, gamma, risk_lambda)\n",
    "\n",
    "part_2 = list(B_vec)\n",
    "try:\n",
    "    part2 = \" \".join(map(repr, part_2))\n",
    "except TypeError:\n",
    "    part2 = repr(part_2)\n",
    "\n",
    "\n",
    "submissions[all_parts[1]]=part2\n",
    "grading.submit(COURSERA_EMAIL, COURSERA_TOKEN, assignment_key,all_parts[:2],all_parts,submissions)\n",
    "\n",
    "B_vec\n",
    "### GRADED PART (DO NOT EDIT) ###"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute optimal hedge and portfolio value"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Call *function_A* and *function_B* for $t=T-1,...,0$ together with basis function $\\Phi_n\\left(X_t\\right)$ to compute optimal action $a_t^\\star\\left(X_t\\right)=\\sum_n^N{\\phi_{nt}\\Phi_n\\left(X_t\\right)}$ backward recursively with terminal condition $a_T^\\star\\left(X_T\\right)=0$.\n",
    "\n",
    "Once the optimal hedge $a_t^\\star\\left(X_t\\right)$ is computed, the portfolio value $\\Pi_t$ could also be computed backward recursively by \n",
    "\n",
    "$$\\Pi_t=\\gamma\\left[\\Pi_{t+1}-a_t^\\star\\Delta S_t\\right]\\quad t=T-1,...,0$$\n",
    "\n",
    "together with the terminal condition $\\Pi_T=H_T\\left(S_T\\right)=\\max\\left(K-S_T,0\\right)$ for a European put option.\n",
    "\n",
    "Also compute $\\hat{\\Pi}_t=\\Pi_t-\\bar{\\Pi}_t$, where $\\bar{\\Pi}_t$ is the sample mean of all values of $\\Pi_t$.\n",
    "\n",
    "Plots of 5 optimal hedge $a_t^\\star$ and portfolio value $\\Pi_t$ paths are shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/ipykernel/__main__.py:22: FutureWarning: reshape is deprecated and will raise in a subsequent release. Please use .values.reshape(...) instead\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computational time: 0.5188488960266113 seconds\n"
     ]
    }
   ],
   "source": [
    "starttime = time.time()\n",
    "\n",
    "# portfolio value\n",
    "Pi = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "Pi.iloc[:,-1] = S.iloc[:,-1].apply(lambda x: terminal_payoff(x, K))\n",
    "\n",
    "Pi_hat = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "Pi_hat.iloc[:,-1] = Pi.iloc[:,-1] - np.mean(Pi.iloc[:,-1])\n",
    "\n",
    "# optimal hedge\n",
    "a = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "a.iloc[:,-1] = 0\n",
    "\n",
    "reg_param = 1e-3 # free parameter\n",
    "for t in range(T-1, -1, -1):\n",
    "    A_mat = function_A_vec(t, delta_S_hat, data_mat_t, reg_param)\n",
    "    B_vec = function_B_vec(t, Pi_hat, delta_S_hat, S, data_mat_t, gamma, risk_lambda)\n",
    "    # print ('t =  A_mat.shape = B_vec.shape = ', t, A_mat.shape, B_vec.shape)\n",
    "    \n",
    "    # coefficients for expansions of the optimal action\n",
    "    phi = np.dot(np.linalg.inv(A_mat), B_vec)\n",
    "    \n",
    "    a.loc[:,t] = np.dot(data_mat_t[t,:,:],phi)\n",
    "    Pi.loc[:,t] = gamma * (Pi.loc[:,t+1] - a.loc[:,t] * delta_S.loc[:,t])\n",
    "    Pi_hat.loc[:,t] = Pi.loc[:,t] - np.mean(Pi.loc[:,t])\n",
    "    \n",
    "a = a.astype('float')\n",
    "Pi = Pi.astype('float')\n",
    "Pi_hat = Pi_hat.astype('float')\n",
    "\n",
    "endtime = time.time()\n",
    "print('Computational time:', endtime - starttime, 'seconds')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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T5ffAO1auzbibVnUblxSmENOkxjojnTcbPyTZlUySMYkDjgOsqFxBYX0hQRkk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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f458ef6c0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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HN0Wl69PQ7CdCSvmulDJFSpkSERHR0eEUijaTtqGINR+mEdM3iKseHtliUI9Wp2H23UPR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\n5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0hFRQWRSITCwsKeTkqfwuv18vLLL1NbW8s3vvGNY1wCxmIxQqEQ4XC4NTw+3iLcx4v3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\nEnSFQqHoIyhBVygUij7C/wfWxBMWY4HVYAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4588184c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot 10 paths\n",
    "plt.plot(a.T.iloc[:,idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.title('Optimal Hedge')\n",
    "plt.show()\n",
    "\n",
    "plt.plot(Pi.T.iloc[:,idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.title('Portfolio Value')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compute rewards for all paths"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once the optimal hedge $a_t^\\star$ and portfolio value $\\Pi_t$ are all computed, the reward function $R_t\\left(X_t,a_t,X_{t+1}\\right)$ could then be computed by\n",
    "\n",
    "$$R_t\\left(X_t,a_t,X_{t+1}\\right)=\\gamma a_t\\Delta S_t-\\lambda Var\\left[\\Pi_t\\space|\\space\\mathcal F_t\\right]\\quad t=0,...,T-1$$\n",
    "\n",
    "with terminal condition $R_T=-\\lambda Var\\left[\\Pi_T\\right]$.\n",
    "\n",
    "Plot of 5 reward function $R_t$ paths is shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Time Cost: 0.13892841339111328 seconds\n"
     ]
    },
    {
     "data": {
      "image/png": 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xJ4zRuWRm3k5N7Rys1pXh81ss3PndnVw09yI+yf+EKalTeO+c95h36TyuH3E9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V1cRvWCYrY/fZhdzx/jyFvtZGXbKastwOHUjUmj2QoLo0p49PX0YIaHkzpjn7SwG2PWhnpcRBYD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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f458ef00ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "# Compute rewards for all paths\n",
    "starttime = time.time()\n",
    "# reward function\n",
    "R = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "R.iloc[:,-1] = - risk_lambda * np.var(Pi.iloc[:,-1])\n",
    "\n",
    "for t in range(T):\n",
    "    R.loc[1:,t] = gamma * a.loc[1:,t] * delta_S.loc[1:,t] - risk_lambda * np.var(Pi.loc[1:,t])\n",
    "\n",
    "endtime = time.time()\n",
    "print('\\nTime Cost:', endtime - starttime, 'seconds')\n",
    "  \n",
    "# plot 10 paths\n",
    "plt.plot(R.T.iloc[:, idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.title('Reward Function')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Part 2: Compute the optimal Q-function with the DP approach \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Coefficients for expansions of the optimal Q-function $Q_t^\\star\\left(X_t,a_t^\\star\\right)$ are solved by\n",
    "\n",
    "$$\\omega_t=\\mathbf C_t^{-1}\\mathbf D_t$$\n",
    "\n",
    "where $\\mathbf C_t$ and $\\mathbf D_t$ are matrix and vector respectively with elements given by\n",
    "\n",
    "$$C_{nm}^{\\left(t\\right)}=\\sum_{k=1}^{N_{MC}}{\\Phi_n\\left(X_t^k\\right)\\Phi_m\\left(X_t^k\\right)}\\quad\\quad D_n^{\\left(t\\right)}=\\sum_{k=1}^{N_{MC}}{\\Phi_n\\left(X_t^k\\right)\\left(R_t\\left(X_t,a_t^\\star,X_{t+1}\\right)+\\gamma\\max_{a_{t+1}\\in\\mathcal{A}}Q_{t+1}^\\star\\left(X_{t+1},a_{t+1}\\right)\\right)}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define function *function_C* and *function_D* to compute the value of matrix $\\mathbf C_t$ and vector $\\mathbf D_t$.\n",
    "\n",
    "**Instructions:**\n",
    "- implement function_C_vec() which computes $C_{nm}^{\\left(t\\right)}$ matrix\n",
    "- implement function_D_vec() which computes $D_n^{\\left(t\\right)}$ column vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def function_C_vec(t, data_mat, reg_param):\n",
    "    \"\"\"\n",
    "    function_C_vec - calculate C_{nm} matrix from Eq. (56) (with a regularization!)\n",
    "    Eq. (56) in QLBS Q-Learner in the Black-Scholes-Merton article\n",
    "    \n",
    "    Arguments:\n",
    "    t - time index, a scalar, an index into time axis of data_mat \n",
    "    data_mat - pandas.DataFrame of values of basis functions of dimension T x N_MC x num_basis\n",
    "    reg_param - regularization parameter, a scalar\n",
    "    \n",
    "    Return:\n",
    "    C_mat - np.array of dimension num_basis x num_basis\n",
    "    \"\"\"\n",
    "    ### START CODE HERE ### (≈ 5-6 lines of code)\n",
    "    # your code here ....\n",
    "    # C_mat = your code here ...\n",
    "    X_mat = data_mat[t, :, :]\n",
    "    num_basis_funcs = X_mat.shape[1]\n",
    "    C_mat = np.dot(X_mat.T, X_mat) + reg_param * np.eye(num_basis_funcs)\n",
    "    ### END CODE HERE ###\n",
    "    return C_mat\n",
    "   \n",
    "def function_D_vec(t, Q, R, data_mat, gamma=gamma):\n",
    "    \"\"\"\n",
    "    function_D_vec - calculate D_{nm} vector from Eq. (56) (with a regularization!)\n",
    "    Eq. (56) in QLBS Q-Learner in the Black-Scholes-Merton article\n",
    "    \n",
    "    Arguments:\n",
    "    t - time index, a scalar, an index into time axis of data_mat \n",
    "    Q - pandas.DataFrame of Q-function values of dimension N_MC x T\n",
    "    R - pandas.DataFrame of rewards of dimension N_MC x T\n",
    "    data_mat - pandas.DataFrame of values of basis functions of dimension T x N_MC x num_basis\n",
    "    gamma - one time-step discount factor $exp(-r \\delta t)$\n",
    "    \n",
    "    Return:\n",
    "    D_vec - np.array of dimension num_basis x 1\n",
    "    \"\"\"\n",
    "    \n",
    "    ### START CODE HERE ### (≈ 5-6 lines of code)\n",
    "    # your code here ....\n",
    "    # D_vec = your code here ...\n",
    "    X_mat = data_mat[t, :, :]\n",
    "    D_vec = np.dot(X_mat.T, R.loc[:,t] + gamma * Q.loc[:, t+1])\n",
    "    ### END CODE HERE ###\n",
    "    return D_vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submission successful, please check on the coursera grader page for the status\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([  1.09774699e+03,   2.10343651e+02,   4.56877655e+00,\n",
       "         8.41911156e+02,   8.69395802e+02,   1.09774699e+03,\n",
       "         3.30191775e+01,   3.53203253e+01,   1.09774699e+03,\n",
       "         4.56877655e+00,   4.56877655e+00,   8.41911156e+02,\n",
       "         8.69395802e+02,   2.10343651e+02,   8.41911156e+02,\n",
       "         8.41911156e+02,   3.53203253e+01,   1.10328718e+03,\n",
       "         8.69395802e+02,   4.35986560e+00,   8.41911156e+02,\n",
       "         1.04949534e+00,   1.10328718e+03,   4.35986560e+00,\n",
       "         1.04949534e+00,   8.69395802e+02,   2.34165631e+00,\n",
       "         1.04949534e+00,   3.30191775e+01,   1.10328718e+03,\n",
       "         1.04949534e+00,   1.99059232e+02,   2.34165631e+00,\n",
       "         4.56877655e+00,   4.56877655e+00,   3.30191775e+01,\n",
       "         1.04949534e+00,   1.04949534e+00,   3.53203253e+01,\n",
       "         1.04949534e+00,   1.09774699e+03,   2.10343651e+02,\n",
       "         1.99059232e+02,   3.53203253e+01,   8.69395802e+02,\n",
       "         3.53203253e+01,   1.09774699e+03,   8.69395802e+02,\n",
       "         1.99059232e+02,   1.09774699e+03])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### GRADED PART (DO NOT EDIT) ###\n",
    "C_mat = function_C_vec(T-1, data_mat_t, reg_param)\n",
    "np.random.seed(42)\n",
    "idx_row = np.random.randint(low=0, high=C_mat.shape[0], size=50)\n",
    "\n",
    "np.random.seed(42)\n",
    "idx_col = np.random.randint(low=0, high=C_mat.shape[1], size=50)\n",
    "\n",
    "part_3 = list(C_mat[idx_row, idx_col])\n",
    "try:\n",
    "    part3 = \" \".join(map(repr, part_3))\n",
    "except TypeError:\n",
    "    part3 = repr(part_3)\n",
    "\n",
    "\n",
    "submissions[all_parts[2]]=part3\n",
    "grading.submit(COURSERA_EMAIL, COURSERA_TOKEN, assignment_key,all_parts[:3],all_parts,submissions)\n",
    "\n",
    "C_mat[idx_row, idx_col]\n",
    "### GRADED PART (DO NOT EDIT) ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submission successful, please check on the coursera grader page for the status\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ -1.33721037e+02,  -5.99514760e+02,  -3.18661973e+03,\n",
       "        -1.02120353e+04,  -1.76323018e+04,  -7.20169691e+03,\n",
       "        -1.13250111e+03,  -1.66673355e+02,  -5.20254025e+01,\n",
       "        -1.55950276e+01,  -5.86197625e+00,  -4.96858215e+00])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### GRADED PART (DO NOT EDIT) ###\n",
    "Q = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "Q.iloc[:,-1] = - Pi.iloc[:,-1] - risk_lambda * np.var(Pi.iloc[:,-1])\n",
    "D_vec = function_D_vec(T-1, Q, R, data_mat_t,gamma)\n",
    "\n",
    "\n",
    "part_4 = list(D_vec)\n",
    "try:\n",
    "    part4 = \" \".join(map(repr, part_4))\n",
    "except TypeError:\n",
    "    part4 = repr(part_4)\n",
    "\n",
    "\n",
    "submissions[all_parts[3]]=part4\n",
    "grading.submit(COURSERA_EMAIL, COURSERA_TOKEN, assignment_key,all_parts[:4],all_parts,submissions)\n",
    "\n",
    "D_vec\n",
    "### GRADED PART (DO NOT EDIT) ###"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Call *function_C* and *function_D* for $t=T-1,...,0$ together with basis function $\\Phi_n\\left(X_t\\right)$ to compute optimal action Q-function $Q_t^\\star\\left(X_t,a_t^\\star\\right)=\\sum_n^N{\\omega_{nt}\\Phi_n\\left(X_t\\right)}$ backward recursively with terminal condition $Q_T^\\star\\left(X_T,a_T=0\\right)=-\\Pi_T\\left(X_T\\right)-\\lambda Var\\left[\\Pi_T\\left(X_T\\right)\\right]$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Time Cost: 0.2546718120574951 seconds\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ou9SGq9SGu8SGq9ROzalKFKvr7EK0AtzSY8IZHoOpXyRa8/ndFhv0PN1uFi1axIEDBxg+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Pv+Vy7Q2XSRHQ8twxFjn3AbSWmxxCU5NOgrFU7puYmUXpfDkTdrKX/6zKyreQ68doGOxotc9+DS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f45880877f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "starttime = time.time()\n",
    "\n",
    "# Q function\n",
    "Q = pd.DataFrame([], index=range(1, N_MC+1), columns=range(T+1))\n",
    "Q.iloc[:,-1] = - Pi.iloc[:,-1] - risk_lambda * np.var(Pi.iloc[:,-1])\n",
    "\n",
    "reg_param = 1e-3\n",
    "for t in range(T-1, -1, -1):\n",
    "    ######################\n",
    "    C_mat = function_C_vec(t,data_mat_t,reg_param)\n",
    "    D_vec = function_D_vec(t, Q,R,data_mat_t,gamma)\n",
    "    omega = np.dot(np.linalg.inv(C_mat), D_vec)\n",
    "    \n",
    "    Q.loc[:,t] = np.dot(data_mat_t[t,:,:], omega)\n",
    "    \n",
    "Q = Q.astype('float')\n",
    "endtime = time.time()\n",
    "print('\\nTime Cost:', endtime - starttime, 'seconds')\n",
    "\n",
    "# plot 10 paths\n",
    "plt.plot(Q.T.iloc[:, idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.title('Optimal Q-Function')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The QLBS option price is given by $C_t^{\\left(QLBS\\right)}\\left(S_t,ask\\right)=-Q_t\\left(S_t,a_t^\\star\\right)$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary of the QLBS pricing and comparison with the BSM pricing "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the QLBS price to European put price given by Black-Sholes formula.\n",
    "\n",
    "$$C_t^{\\left(BS\\right)}=Ke^{-r\\left(T-t\\right)}\\mathcal N\\left(-d_2\\right)-S_t\\mathcal N\\left(-d_1\\right)$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# The Black-Scholes prices\n",
    "def bs_put(t, S0=S0, K=K, r=r, sigma=sigma, T=M):\n",
    "    d1 = (np.log(S0/K) + (r + 1/2 * sigma**2) * (T-t)) / sigma / np.sqrt(T-t)\n",
    "    d2 = (np.log(S0/K) + (r - 1/2 * sigma**2) * (T-t)) / sigma / np.sqrt(T-t)\n",
    "    price = K * np.exp(-r * (T-t)) * norm.cdf(-d2) - S0 * norm.cdf(-d1)\n",
    "    return price\n",
    "\n",
    "def bs_call(t, S0=S0, K=K, r=r, sigma=sigma, T=M):\n",
    "    d1 = (np.log(S0/K) + (r + 1/2 * sigma**2) * (T-t)) / sigma / np.sqrt(T-t)\n",
    "    d2 = (np.log(S0/K) + (r - 1/2 * sigma**2) * (T-t)) / sigma / np.sqrt(T-t)\n",
    "    price = S0 * norm.cdf(d1) - K * np.exp(-r * (T-t)) * norm.cdf(d2)\n",
    "    return price\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The DP solution for QLBS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-------------------------------------------\n",
      "       QLBS Option Pricing (DP solution)      \n",
      "-------------------------------------------\n",
      "\n",
      "Initial Stock Price:      100\n",
      "Drift of Stock:           0.05\n",
      "Volatility of Stock:      0.15\n",
      "Risk-free Rate:           0.03\n",
      "Risk aversion parameter:  0.001\n",
      "Strike:                   100\n",
      "Maturity:                 1\n",
      "\n",
      "QLBS Put Price:           4.9261\n",
      "\n",
      "Black-Sholes Put Price:   4.5296\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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/nfT0R3A6Ozhd8id271nB/gP30tXl/82UDRs2oNVque6663A4rFgs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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f4588087748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# QLBS option price\n",
    "C_QLBS = - Q.copy()\n",
    "\n",
    "print('-------------------------------------------')\n",
    "print('       QLBS Option Pricing (DP solution)      ')\n",
    "print('-------------------------------------------\\n')\n",
    "print('%-25s' % ('Initial Stock Price:'), S0)\n",
    "print('%-25s' % ('Drift of Stock:'), mu)\n",
    "print('%-25s' % ('Volatility of Stock:'), sigma)\n",
    "print('%-25s' % ('Risk-free Rate:'), r)\n",
    "print('%-25s' % ('Risk aversion parameter: '), risk_lambda)\n",
    "print('%-25s' % ('Strike:'), K)\n",
    "print('%-25s' % ('Maturity:'), M)\n",
    "print('%-26s %.4f' % ('\\nQLBS Put Price: ', C_QLBS.iloc[0,0]))\n",
    "print('%-26s %.4f' % ('\\nBlack-Sholes Put Price:', bs_put(0)))\n",
    "print('\\n')\n",
    "\n",
    "# plot 10 paths\n",
    "plt.plot(C_QLBS.T.iloc[:,idx_plot])\n",
    "plt.xlabel('Time Steps')\n",
    "plt.title('QLBS Option Price')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Submission successful, please check on the coursera grader page for the status\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "4.926125422031383"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### GRADED PART (DO NOT EDIT) ###\n",
    "\n",
    "part5 = str(C_QLBS.iloc[0,0])\n",
    "submissions[all_parts[4]]=part5\n",
    "grading.submit(COURSERA_EMAIL, COURSERA_TOKEN, assignment_key,all_parts[:5],all_parts,submissions)\n",
    "\n",
    "C_QLBS.iloc[0,0]\n",
    "### GRADED PART (DO NOT EDIT) ###"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### make a summary picture"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+ntCfR3s1VxW4yk2J0WBgwzczsLZ3YMhzr1QbL74gnrnH5jIqZBQf3fZRtQr8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VOYVUvBgVoqjjXhckmMIb6kjY8gfVIUcSNC+rT7bdsHx8n6rJThU6O54r7RPQ7ReC4+e+MIR7ZV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o7fcCMtf/kLjrY2Wp55FtnXR9wdY/sfEEj1Fa7/A2MZDwcICTcQZQk7b3KbN0UsWQI2G127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\nSKkkriiKoihB6v8DhuTapkgj9msAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f458817a550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot: Simulated S_t and X_t values\n",
    "# optimal hedge and portfolio values\n",
    "# rewards and optimal Q-function\n",
    "\n",
    "f, axarr = plt.subplots(3, 2)\n",
    "f.subplots_adjust(hspace=.5)\n",
    "f.set_figheight(8.0)\n",
    "f.set_figwidth(8.0)\n",
    "\n",
    "axarr[0, 0].plot(S.T.iloc[:,idx_plot]) \n",
    "axarr[0, 0].set_xlabel('Time Steps')\n",
    "axarr[0, 0].set_title(r'Simulated stock price  $S_t$')\n",
    "\n",
    "axarr[0, 1].plot(X.T.iloc[:,idx_plot]) \n",
    "axarr[0, 1].set_xlabel('Time Steps')\n",
    "axarr[0, 1].set_title(r'State variable $X_t$')\n",
    "\n",
    "axarr[1, 0].plot(a.T.iloc[:,idx_plot]) \n",
    "axarr[1, 0].set_xlabel('Time Steps')\n",
    "axarr[1, 0].set_title(r'Optimal action $a_t^{\\star}$')\n",
    "\n",
    "axarr[1, 1].plot(Pi.T.iloc[:,idx_plot]) \n",
    "axarr[1, 1].set_xlabel('Time Steps')\n",
    "axarr[1, 1].set_title(r'Optimal portfolio $\\Pi_t$')\n",
    "\n",
    "axarr[2, 0].plot(R.T.iloc[:,idx_plot]) \n",
    "axarr[2, 0].set_xlabel('Time Steps')\n",
    "axarr[2, 0].set_title(r'Rewards $R_t$') \n",
    "\n",
    "axarr[2, 1].plot(Q.T.iloc[:,idx_plot]) \n",
    "axarr[2, 1].set_xlabel('Time Steps')\n",
    "axarr[2, 1].set_title(r'Optimal DP Q-function $Q_t^{\\star}$')\n",
    "\n",
    "\n",
    "# plt.savefig('QLBS_DP_summary_graphs_ATM_option_mu=r.png', dpi=600)\n",
    "# plt.savefig('QLBS_DP_summary_graphs_ATM_option_mu>r.png', dpi=600)\n",
    "plt.savefig('QLBS_DP_summary_graphs_ATM_option_mu>r.png', dpi=600)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Tz77EpLfepffWewHw0bRPOPiIk7jh2t8tbg1VqUpQAHvv0Zce3dfk9Ylvs2vf7ZdYbt0e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\nIoiIj0mGs+6dFu0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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f45759d2048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot convergence to the Black-Scholes values\n",
    "\n",
    "# lam = 0.0001, Q = 4.1989 +/- 0.3612 # 4.378\n",
    "# lam = 0.001: Q = 4.9004 +/- 0.1206  # Q=6.283\n",
    "# lam = 0.005: Q = 8.0184 +/- 0.9484 # Q = 14.7489\n",
    "# lam = 0.01: Q = 11.9158 +/- 2.2846 # Q = 25.33\n",
    "\n",
    "lam_vals = np.array([0.0001, 0.001, 0.005, 0.01])\n",
    "# Q_vals =  np.array([3.77, 3.81, 4.57, 7.967,12.2051])\n",
    "Q_vals =  np.array([4.1989, 4.9004, 8.0184, 11.9158])\n",
    "Q_std =  np.array([0.3612,0.1206, 0.9484, 2.2846])\n",
    "\n",
    "BS_price = bs_put(0)\n",
    "\n",
    "# f, axarr = plt.subplots(1, 1)\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "\n",
    "f.subplots_adjust(hspace=.5)\n",
    "f.set_figheight(4.0)\n",
    "f.set_figwidth(4.0)\n",
    "\n",
    "# ax.plot(lam_vals,Q_vals) \n",
    "ax.errorbar(lam_vals, Q_vals, yerr=Q_std, fmt='o')\n",
    "\n",
    "ax.set_xlabel('Risk aversion')\n",
    "ax.set_ylabel('Optimal option price')\n",
    "ax.set_title(r'Optimal option price vs risk aversion')\n",
    "ax.axhline(y=BS_price,linewidth=2, color='r')\n",
    "textstr = 'BS price = %2.2f'% (BS_price)\n",
    "props = dict(boxstyle='round', facecolor='wheat', alpha=0.5)                      \n",
    "# place a text box in upper left in axes coords\n",
    "ax.text(0.05, 0.95, textstr, fontsize=11,transform=ax.transAxes, verticalalignment='top', bbox=props)\n",
    "plt.savefig('Opt_price_vs_lambda_Markowitz.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "coursera": {
   "course_slug": "reinforcement-learning-in-finance"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
